Nowadays, there are a wide variety of products available in market. End users, technicians and the like, who purchase the products, may not know every feature of the products and working of every feature of the products. The users may experience difficulties in operating the products in their day to day lives. To overcome this problem, every product is associated with documents such as a user manual, frequently asked questions and the like. These documents include information related to usability of the product, troubleshooting issues related to the product, services provided for the product and the like. However, the end user may have to search through these bulky documents to find a solution to any issue that he might be facing with respect to the product. Further, there may exist same string related to an issue in multiple places of the document that makes the search process cumbersome for the end user. Due to such difficult procedure involved, the end user may call the helpdesk or walk-in to a customer care proximal to his location for resolving simple issues. However, there are instances where the customer care is shutdown or technical experts in the customer care may not he available. In few other instances, the technical experts may not be able to understand the issue to resolve. Therefore, even the technical experts may have to search through the bulky documents with a keyword constraint, thereby leading to additional difficulties in identifying the issue. In few other instances, the issue may be understood but due to complexity of the issue, assistance of the technical experts from far off locations may be required, thereby leading to delay in resolving the issue. The end user may lose interest in the product due to the hectic process of resolving the issue.
Existing techniques provide virtual helpdesks that extract keywords and synonyms of the keywords from a user query and search for a question that matches the user query exactly in a database. However, if the user query does not match any question, virtual assistance cannot be provided to the end user. In few other existing techniques, massive ontologies are utilized for understanding the user query, but these ontologies may be static that do not scale over time. Also, the existing techniques require maximum human supervision for resolving the issue.